Update README.md

README.md

@@ -64,7 +64,20 @@ model = GLiNER.from_pretrained("nvidia/gliner-pii")
 
 # Sample text containing PII/PHI entities
 text = """
+   **Claim Denial Letter**
 
+   **Date:** 2023-11-15
+
+   **Claimant Information:**
+   - **Claimant Name:** Nataly White
+   - **Medical Record Number:** 1842-75-3924
+
+   **Claim Denial Details:**
+
+   Dear Nataly White,
+
+   We are writing to inform you that your disability claim has been denied. The denial is based on the information provided in your medical record, numbered 1842-75-3924.
+   After a thorough review, it has been determined that the medical evidence does not meet the criteria outlined in your policy for disability benefits.
 """
 
 # Define the labels for PII/PHI entities
@@ -131,4 +144,58 @@ entities = model.predict_entities(text, labels, threshold=0.3)
 
 # Display the detected entities
 print(json.dumps(entities, indent=2))
-```
+
+# Expected output:
+[
+  {
+    "start": 42,
+    "end": 52,
+    "text": "2023-11-15",
+    "label": "date",
+    "score": 0.9999942779541016
+  },
+  {
+    "start": 107,
+    "end": 113,
+    "text": "Nataly",
+    "label": "first_name",
+    "score": 0.9999998807907104
+  },
+  {
+    "start": 114,
+    "end": 119,
+    "text": "White",
+    "label": "last_name",
+    "score": 0.9999997615814209
+  },
+  {
+    "start": 152,
+    "end": 164,
+    "text": "1842-75-3924",
+    "label": "medical_record_number",
+    "score": 0.9999996423721313
+  },
+  {
+    "start": 204,
+    "end": 210,
+    "text": "Nataly",
+    "label": "first_name",
+    "score": 0.9999998807907104
+  },
+  {
+    "start": 211,
+    "end": 216,
+    "text": "White",
+    "label": "last_name",
+    "score": 0.9999998807907104
+  },
+  {
+    "start": 376,
+    "end": 388,
+    "text": "1842-75-3924",
+    "label": "medical_record_number",
+    "score": 0.999998927116394
+  }
+]
+```
+